To search for text, images, ideas, websites, etc., on the Internet or in a computing device, a text keyword can be entered to commence the search. Conventionally, searching for an image in a computing environment is limited to entering a text keyword that summarizes the image or entering text that summarizes a visual object or visual characteristic of the image. Conventionally, it has been difficult to search for an image without translating some a key part of the searching to text. Thus, conventional image searches are really text searches.
The difficulty of performing successful image searches lies in the images themselves. An image is far more complex than a word. This is because an image can be modified such that the modified image is mathematically different than the original, yet to the human visual system the two images are visually indistinguishable from each other. Thus, if a user lightens or darkens an image, changes the contrast, fine-tunes the colors, crops, or compresses the image, etc., then parameters that quantify the image have significantly changed, even though the image may appear the same. To avoid this complexity, it has been easier just to summarize the picture with words and then perform a word search for the picture.
What is needed is a way to capture an image mathematically—informationally—so that an image search can be commenced by entering the image itself, and successfully concluded by finding matching versions of the image that may have been modified in many different ways, e.g., by image editing software.